The concept of gathering data to make a difference isn’t new. The theory of big data has been around since the Victorian era, when data was used to map out sewers and wells to prevent the spread of disease, and we’re still trying to achieve the same outcomes today as our ancestors were back then. However, now, we’re able to do it more quickly and efficiently through the use of fit-for-purpose technology. For example, in times of crisis, our doctors and nurses can now send data across the world to be analysed and have the results within seconds, whereas physicians in the 1800s had to painstakingly gather and manually analyse observations and data over a long period of time in order to make a difference for patients. As a result of our advancing technology, the questions around big data are going beyond what data is gathered to where the data is gathered and how it is used. These questions can be answered by looking at the three main concepts behind big data analytics, which you can simply remember as your ABCs – access, benefits, and collaboration.
Society accesses enormous quantities of data every day. Every minute, Google receives over four million search queries, Facebook users share nearly 2.5 million pieces of content and email users send over 200 million messages. Imagine your daily routine – you wake up, check your news feeds, eat breakfast, check the train timetable, board the train and log onto public Wi-Fi on your way to work. We know that these seemingly small activities result in a huge amount of data that needs to be processed and we’ve become used to seeing quick-fire analytics on our Twitter dashboards. This trend has led business executives to wonder why they don’t have that same kind of access from their business intelligence solutions.
Current market perspective tends to cite data as too large and complex for on-hand database management tools or traditional data processing applications to manage. However, rather than ripping and replacing every time a new marketing push makes you want that new and flashy piece of kit, take a step back to assess your business objectives and align your big data initiatives to your organisation’s goals. That way you can ensure you provide the access needed to data insights to improve day-to-day work.
Once you have access to the insights, data analytics can help raise your business to the next level. We’ve all been in the position where your client or CEO turns to you and says, “Show me the numbers.” Demonstration of results through quantitative data can be crucial to closing a sale or convincing your boss to spring for a new hire or programme. But beyond the initial validation for your work, big data analytics can reduce costs and lead to faster and better decision making across the business, and inspire new products and services.
Budgets are a constant grievance for IT managers and a simple price comparison between most big data analytics technology and traditional architectures will show the clear benefit of taking a future-ready approach to analytics. Once that technology is in place, decision making can be sped up and conducted with increased accuracy, an impact that will ultimately be reflected in the bottom line. Finally, and perhaps most importantly, big data analytics can be used to create new products and services for customers. Once you understand exactly what your customers want by analysing usage, buying trends and feedback, you can tailor your offerings to suit.
Most people do not like the idea of someone else having access to their data and thus having the ability to analyse it. However, as the benefits of divulging certain information starts becoming clear to you in better customer service or increased usability, it becomes easier to come to terms with companies having that information. As a business, it should be a key priority to work collaboratively with your customers in order to improve your company for the future. Create opportunities for customers to selectively share information so that they feel they have control but you are still able to gather the insights that you need to better your service or product. Once a grounding of trust exists, more and more insights will become available and go towards shaping your future strategies.
With technology constantly changing and data continuing to deluge businesses, implementing a future-ready strategy is crucial. In terms of big data analytics, this means building predictive models and working collaboratively to set the context. It’s becoming abundantly clear that the old ways of measuring success will ultimately result in failure without adaption. In 2016, take a minute to remember your ABCs and move your big data analytics into the future.
Paul Brook, EMEA Team Lead: Big Data & Cloud, Dell
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